Triple
T8604773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lumut Port |
E203769
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Lumut, Perak |
E206262
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lumut, Perak | Statement: [Lumut Port, locatedNear, Lumut, Perak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lumut, Perak Context triple: [Lumut Port, locatedNear, Lumut, Perak]
-
A.
Lumut
chosen
Lumut is a coastal town in the Malaysian state of Perak, known as a gateway to Pangkor Island and as a naval and port town.
-
B.
Lumut
Lumut is a small island located within Indonesia’s Bangka Belitung Islands province, known for its coastal tropical setting.
-
C.
Kuala Kangsar
Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
-
D.
Sitiawan, Perak
Sitiawan, Perak is a coastal town in the Manjung District of Perak, Malaysia, known historically for its Chinese settler communities and as a gateway to the nearby Pangkor Island.
-
E.
Kuala Perlis
Kuala Perlis is a small coastal town in Malaysia known as a key ferry gateway to the resort island of Langkawi.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46dd8ff8819081ef269192047488 |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea900cf708190abb550f592edbdf6 |
completed | April 2, 2026, 5:36 p.m. |
Created at: March 30, 2026, 6:24 p.m.